87,772 research outputs found
T-duality Twists and Asymmetric Orbifolds
We study some aspects of asymmetric orbifolds of tori, with the orbifold
group being some subgroup of the T-duality group and, in
particular, provide a concrete understanding of certain phase factors that may
accompany the T-duality operation on the stringy Hilbert space in toroidal
compactification. We discuss how these T-duality twist phase factors are
related to the symmetry and locality properties of the closed string vertex
operator algebra, and clarify the role that they enact in the modular
covariance of the orbifold theory, mainly using asymmetric orbifolds of tori
which are root lattices as working examples.Comment: 67 pages. v2: references added and typos correcte
Thin-shell deployable reflectors with collapsible stiffeners: part 1 - approach
Thin-shell deployable reflector structures that are folded elastically in a nearly inextensional mode have been recently realized, exploiting the recent availability of high-modulus, ultrathin composite materials. An inherent and significant limitation of this approach is that these structures remain āfloppyā in their deployed configuration. This paper presents a general concept for increasing the deployed stiffness of such structures, through the addition of a collapsible edge stiffener around the rim of a reflector dish. Ananalytical expression of the frequency/stiffness related to the softest deformation mode of a thin-shell reflector structure is presented, both with and without the stiffener. During folding, the stiffener collapses elastically, and this behavior is facilitated by the introduction of suitable discontinuities within the stiffener, or between the dish and the stiffener. A detailed study of a range of different options is presented, and one particular scheme is selected and optimized. For a specific example, a stiffness increase by a factor of 31 and a fundamental frequency increase by a factor of 4 are achieved, with a mass increase of only 16%
AlAsSb avalanche photodiodes with a sub-mV/K temperature coefficient of breakdown voltage
The temperature dependence of dark current and avalanche gain were measured on AlAsSb p-i-n diodes with avalanche region widths of 80 and 230 nm. Measurements at temperatures ranging from 77 to 295 K showed that the dark current decreases rapidly with reducing temperature while avalanche gain exhibits a weak temperature dependence. No measurable band to band tunneling current was observed in the thinner diodes at an electric field of 1.07 MV/cm, corresponding to a bias of 95% of the breakdown voltage. Temperature coefficients of breakdown voltage of 0.95 and 1.47 mV/K were obtained from 80 and 230 nm diodes, respectively. These are significantly lower than a range of semiconductor materials with similar avalanche region widths. Our results demonstrated the potential of using thin AlAsSb avalanche regions to achieve low temperature coefficient of breakdown voltage without suffering from high band to band tunneling current
Efficient data augmentation techniques for some classes of state space models
Data augmentation improves the convergence of iterative algorithms, such as
the EM algorithm and Gibbs sampler by introducing carefully designed latent
variables. In this article, we first propose a data augmentation scheme for the
first-order autoregression plus noise model, where optimal values of working
parameters introduced for recentering and rescaling of the latent states, can
be derived analytically by minimizing the fraction of missing information in
the EM algorithm. The proposed data augmentation scheme is then utilized to
design efficient Markov chain Monte Carlo (MCMC) algorithms for Bayesian
inference of some non-Gaussian and nonlinear state space models, via a mixture
of normals approximation coupled with a block-specific reparametrization
strategy. Applications on simulated and benchmark real datasets indicate that
the proposed MCMC sampler can yield improvements in simulation efficiency
compared with centering, noncentering and even the ancillarity-sufficiency
interweaving strategy.Comment: Keywords: Data augmentation, State space model, Stochastic volatility
model, EM algorithm, Reparametrization, Markov chain Monte Carlo,
Ancillarity-sufficiency interweaving strateg
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